138 lines
2.8 KiB
Markdown
138 lines
2.8 KiB
Markdown
# PDF OCR Processing Guide
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Extract text from scanned PDFs and image-based documents.
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## Quick start
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```python
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import pytesseract
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from pdf2image import convert_from_path
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from PIL import Image
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# Convert PDF to images
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images = convert_from_path("scanned.pdf")
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# Extract text from each page
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for i, image in enumerate(images):
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text = pytesseract.image_to_string(image)
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print(f"Page {i+1}:\n{text}\n")
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```
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## Installation
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### Install Tesseract
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**macOS:**
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```bash
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brew install tesseract
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```
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**Ubuntu/Debian:**
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```bash
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sudo apt-get install tesseract-ocr
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```
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**Windows:**
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Download from: https://github.com/UB-Mannheim/tesseract/wiki
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### Install Python packages
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```bash
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pip install pytesseract pdf2image pillow
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```
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## Language support
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```python
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# English (default)
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text = pytesseract.image_to_string(image, lang="eng")
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# Spanish
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text = pytesseract.image_to_string(image, lang="spa")
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# Multiple languages
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text = pytesseract.image_to_string(image, lang="eng+spa+fra")
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```
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Install additional languages:
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```bash
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# macOS
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brew install tesseract-lang
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# Ubuntu
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sudo apt-get install tesseract-ocr-spa tesseract-ocr-fra
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```
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## Image preprocessing
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```python
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from PIL import Image, ImageEnhance, ImageFilter
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def preprocess_for_ocr(image):
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"""Optimize image for better OCR accuracy."""
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# Convert to grayscale
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image = image.convert("L")
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# Increase contrast
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enhancer = ImageEnhance.Contrast(image)
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image = enhancer.enhance(2.0)
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# Denoise
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image = image.filter(ImageFilter.MedianFilter())
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# Sharpen
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image = image.filter(ImageFilter.SHARPEN)
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return image
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# Usage
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image = Image.open("scanned_page.png")
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processed = preprocess_for_ocr(image)
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text = pytesseract.image_to_string(processed)
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```
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## Best practices
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1. **Preprocess images** for better accuracy
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2. **Use appropriate language** models
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3. **Batch process** large documents
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4. **Cache results** to avoid re-processing
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5. **Validate output** - OCR is not 100% accurate
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6. **Consider confidence scores** for quality checks
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## Production example
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```python
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import pytesseract
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from pdf2image import convert_from_path
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from PIL import Image
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def ocr_pdf(pdf_path, output_path):
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"""OCR PDF and save to text file."""
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# Convert to images
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images = convert_from_path(pdf_path, dpi=300)
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full_text = []
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for i, image in enumerate(images, 1):
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print(f"Processing page {i}/{len(images)}")
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# Preprocess
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processed = preprocess_for_ocr(image)
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# OCR
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text = pytesseract.image_to_string(processed, lang="eng")
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full_text.append(f"--- Page {i} ---\n{text}\n")
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# Save
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with open(output_path, "w", encoding="utf-8") as f:
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f.write("\n".join(full_text))
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print(f"Saved to {output_path}")
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# Usage
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ocr_pdf("scanned_document.pdf", "extracted_text.txt")
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```
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